Amazon's controversial face-recognition technology is being tested and used by the Orlando police department, and apparently Congress isn't happy about that. Two members of the House of Representatives, Keith Ellison (D-MN) and Emanuel Cleaver (D-MO), have sent Jeff Bezos a letter demanding he explain exactly how the tech, called Rekognition, is being used by law enforcement. The Intercept was provided a copy of the letter before was publicly released. You can read it for yourself here. In it, they ask Bezos what law enforcement agencies are using the software, who Amazon has offered Rekognition to, information about error rates and bias and how Amazon is making sure its software isn't used to further systems that disproportionately impact protected groups.

Tesla on Thursday reached an agreement to settle a class action lawsuit with buyers of its Model S and Model X cars who alleged that the company's assisted-driving Autopilot system was'essentially unusable and demonstrably dangerous.' The agreement, announced in a filing in San Jose federal court late Thursday, still has to be approved by U.S. District Judge Beth Labson Freeman. Tesla said in a statement it wanted to do right by its customers and, as part of the proposed deal, agreed to compensate car owners who purchased the 2.0 version of Autopilot and had to wait longer than expected for the driving features to become active. Tesla-CEO Elon Musk speaks during the delivery of the first more reasonable Tesla vehicle Model 3 in Fremont. Two U.S. consumer advocacy groups urged the FTC to investigate what they called Tesla's'deceptive and misleading' use of the name Autopilot for its assisted-driving technology.

More and more people are talking about the new economy, and in particular, the role played by robots. As jobs are being eliminated and replaced by robots, governments are losing tax money. There are discussions as to whether robots should be taxed. Most people think of robots as machines with arms and legs: this is the most visible part of artificial intelligence. However, this is only the tip of the iceberg.

File photo - Troopers with the U.S. Army 2nd Armored Brigade Combat Team, 3rd Infantry Division fire the main gun round at a target during unit gunnery practice with newly acquired M1A1-SA Abrams tanks at Fort Stewart, Georgia, U.S. March 29, 2018. Picture taken March 29, 2018. The Army is engineering high-tech autonomy kits designed to give "robot" tanks and other armored combat vehicles an ability to operate with little or no human intervention, bringing new tactical and operational dimensions to the future of ground combat. Unmanned systems, utilized in a fast-evolving, high-threat ground combat operation, could enable robot vehicles to carry supplies, test enemy defenses and even fire weapons – all while manned vehicles operate at a safer distance. "A kit of hardware and software can be installed into different ground platforms to increase the level of autonomy," Osie David, Chief Engineer for Mission Command, Communications-Electronics Research, Development and Engineering Center, told Warrior Maven in an interview.

Modern motion-capture systems are the product of a century of tinkering, innovation and computational advances. Mocap was born a lifetime before Gollum hit the big screen in The Lord of the Rings, and ages before the Cold War, Vietnam War or World War II. It was 1915, in the midst of the First World War, when animator Max Fleischer developed a technique called rotoscoping and laid the foundation for today's cutting-edge mocap technology. Rotoscoping was a primitive and time-consuming process, but it was a necessary starting point for the industry. In the rotoscope method, animators stood at a glass-topped desk and traced over a projected live-action film frame-by-frame, copying actors' or animals' actions directly onto a hand-drawn world.

There is a legitimate renaissance in all things dealing with space. In April, Bloomberg reported the latest funding round for Elon Musk's Space Exploration Technologies placed the value of the privately held rocket company at $25 billion. This should be a wakeup call for investors. A big wave is on the horizon. VANDENBERG AIR FORCE BASE - MAY 22: In this handout image provided by NASA, the NASA/German Research Centre for Geosciences GRACE Follow-On spacecraft launch onboard a SpaceX Falcon 9 rocket, Tuesday, May 22, 2018, from Space Launch Complex 4E at Vandenberg Air Force Base in California.

There are several vignettes: 1.

On a recent work trip, I found myself in a swanky-but-still-hip office of a private tech firm. I was drinking a freshly frothed cappuccino, eyeing a mini-fridge stocked with local beer and standing amidst a group of hoodie-clad software developers typing away diligently at their laptops against a backdrop of Star Wars and xkcd comic wallpaper. I wasn't in Silicon Valley: I was in Johannesburg, South Africa, meeting with a firm that is designing machine learning (ML) tools for a local project backed by the U.S. Agency for International Development. Around the world, tech startups are partnering with NGOs to bring machine learning and artificial intelligence to bear on problems that the international aid sector has wrestled with for decades. ML is uncovering new ways to increase crop yields for rural farmers.

Every single day, the connected world creates 44 exabytes of new data--an amount equal to three million Libraries of Congress--that can be collected, stored, and analyzed. At the same time, artificial intelligence is being applied in new ways that are expected to transform virtually every sector. AI is transforming everything from finance, retail, and healthcare to national security and criminal justice. These rapid advances in technology and data analytics are having far-reaching consequences for jobs, the economy, society, and governance. In this situation, it is vital to think about the policy, legal, and ethical implications of the coming "digitalization of everything".

News Blog China's Perfect Storm AI Moment May 22, 2018 Robin Raskin, Founder, Living in Digital Times In July of 2017 the Chinese government issued a development plan to make the country the world leader in artificial intelligence by 2030. So far things are going better than pretty well. The government's commitment to AI dominance, the sheer amount of data that a country as large as China can feed to its AI learning systems, a mobile-dominated infrastructure, and an edge on chip manufacturing for AI-intensive activities like facial and image recognition contribute to China's AI success story. Deep machine learning, the ability for machines to ingest data, learn from it and then make predictions from it requires lots of data. "There are 160 cities in China with over 1 million people; there are 10 in the U.S., says Deborah Weinswig, Senior Analyst for Fung.